33 citations · 109 across the 23 of their papers we have counts for
26 papers
DualBrep: A Dual-Field Continuous Representation for B-rep Modelling
Yilin Liu, Pradeep Jayaraman, Chinthala Reddy +2
Boundary Representation (B-rep) is the most commonly used data format in Computer-Aided Design (CAD) due to its analytical precision and direct support for parametric editing. Howe…
Zero-to-CAD: Agentic Synthesis of Interpretable CAD Programs at Million-Scale Without Real Data
Mohammadmehdi Ataei, Farzaneh Askari, Kamal Rahimi Malekshan +1
Computer-Aided Design (CAD) models are defined by their construction history: a parametric recipe that encodes design intent. However, existing large-scale 3D datasets predominantl…
Draw it like Euclid: Teaching transformer models to generate CAD profiles using ruler and compass construction steps
Siyi Li, Joseph G. Lambourne, Longfei Zhang +2
We introduce a new method of generating Computer Aided Design (CAD) profiles via a sequence of simple geometric constructions including curve offsetting, rotations and intersection…
AutoBrep: Autoregressive B-Rep Generation with Unified Topology and Geometry
Xiang Xu, Pradeep Kumar Jayaraman, Joseph G. Lambourne +3
The boundary representation (B-Rep) is the standard data structure used in Computer-Aided Design (CAD) for defining solid models. Despite recent progress, directly generating B-Rep…
B-Rep Distance Functions (BR-DF): How to Represent a B-Rep Model by Volumetric Distance Functions?
Fuyang Zhang, Pradeep Kumar Jayaraman, Xiang Xu +1
This paper presents a novel geometric representation for CAD Boundary Representation (B-Rep) based on volumetric distance functions, dubbed B-Rep Distance Functions (BR-DF). BR-DF…
MechaFormer: Sequence Learning for Kinematic Mechanism Design Automation
Diana Bolanos, Mohammadmehdi Ataei, Pradeep Kumar Jayaraman
Designing mechanical mechanisms to trace specific paths is a classic yet notoriously difficult engineering problem, characterized by a vast and complex search space of discrete top…
Aligning Constraint Generation with Design Intent in Parametric CAD
Evan Casey, Tianyu Zhang, Shu Ishida +6
We adapt alignment techniques from reasoning LLMs to the task of generating engineering sketch constraints found in computer-aided design (CAD) models. Engineering sketches consist…
e-SimFT: Alignment of Generative Models with Simulation Feedback for Pareto-Front Design Exploration
Hyunmin Cheong, Mohammadmehdi Ataei, Amir Hosein Khasahmadi +1
Deep generative models have recently shown success in solving complex engineering design problems where models predict solutions that address the design requirements specified as i…
Optimal design of frame structures with mixed categorical and continuous design variables using the Gumbel-Softmax method
Mehran Ebrahimi, Hyunmin Cheong, Pradeep Kumar Jayaraman +1
In optimizing real-world structures, due to fabrication or budgetary restraints, the design variables may be restricted to a set of standard engineering choices. Such variables, co…
3D-WAG: Hierarchical Wavelet-Guided Autoregressive Generation for High-Fidelity 3D Shapes
Tejaswini Medi, Arianna Rampini, Pradyumna Reddy +2
Autoregressive (AR) models have achieved remarkable success in natural language and image generation, but their application to 3D shape modeling remains largely unexplored. Unlike…
CadVLM: Bridging Language and Vision in the Generation of Parametric CAD Sketches
Sifan Wu, Amir Khasahmadi, Mor Katz +4
Parametric Computer-Aided Design (CAD) is central to contemporary mechanical design. However, it encounters challenges in achieving precise parametric sketch modeling and lacks pra…
Deep Generative Model for Mechanical System Configuration Design
Yasaman Etesam, Hyunmin Cheong, Mohammadmehdi Ataei +1
Generative AI has made remarkable progress in addressing various design challenges. One prominent area where generative AI could bring significant value is in engineering design. I…
BrepGen: A B-rep Generative Diffusion Model with Structured Latent Geometry
Xiang Xu, Joseph G. Lambourne, Pradeep Kumar Jayaraman +3
This paper presents BrepGen, a diffusion-based generative approach that directly outputs a Boundary representation (B-rep) Computer-Aided Design (CAD) model. BrepGen represents a B…
Sketch-A-Shape: Zero-Shot Sketch-to-3D Shape Generation
Aditya Sanghi, Pradeep Kumar Jayaraman, Arianna Rampini +4
Significant progress has recently been made in creative applications of large pre-trained models for downstream tasks in 3D vision, such as text-to-shape generation. This motivates…
Hierarchical Neural Coding for Controllable CAD Model Generation
Xiang Xu, Pradeep Kumar Jayaraman, Joseph G. Lambourne +2
This paper presents a novel generative model for Computer Aided Design (CAD) that 1) represents high-level design concepts of a CAD model as a three-level hierarchical tree of neur…
Reconstructing editable prismatic CAD from rounded voxel models
Joseph G. Lambourne, Karl D. D. Willis, Pradeep Kumar Jayaraman +3
Reverse Engineering a CAD shape from other representations is an important geometric processing step for many downstream applications. In this work, we introduce a novel neural net…
SkexGen: Autoregressive Generation of CAD Construction Sequences with Disentangled Codebooks
Xiang Xu, Karl D. D. Willis, Joseph G. Lambourne +3
We present SkexGen, a novel autoregressive generative model for computer-aided design (CAD) construction sequences containing sketch-and-extrude modeling operations. Our model util…
SolidGen: An Autoregressive Model for Direct B-rep Synthesis
Pradeep Kumar Jayaraman, Joseph G. Lambourne, Nishkrit Desai +3
The Boundary representation (B-rep) format is the de-facto shape representation in computer-aided design (CAD) to model solid and sheet objects. Recent approaches to generating CAD…
JoinABLe: Learning Bottom-up Assembly of Parametric CAD Joints
Karl D. D. Willis, Pradeep Kumar Jayaraman, Hang Chu +8
Physical products are often complex assemblies combining a multitude of 3D parts modeled in computer-aided design (CAD) software. CAD designers build up these assemblies by alignin…
UVStyle-Net: Unsupervised Few-shot Learning of 3D Style Similarity Measure for B-Reps
Peter Meltzer, Hooman Shayani, Amir Khasahmadi +3
Boundary Representations (B-Reps) are the industry standard in 3D Computer Aided Design/Manufacturing (CAD/CAM) and industrial design due to their fidelity in representing stylisti…
Engineering Sketch Generation for Computer-Aided Design
Karl D. D. Willis, Pradeep Kumar Jayaraman, Joseph G. Lambourne +2
Engineering sketches form the 2D basis of parametric Computer-Aided Design (CAD), the foremost modeling paradigm for manufactured objects. In this paper we tackle the problem of le…
BRepNet: A topological message passing system for solid models
Joseph G. Lambourne, Karl D. D. Willis, Pradeep Kumar Jayaraman +3
Boundary representation (B-rep) models are the standard way 3D shapes are described in Computer-Aided Design (CAD) applications. They combine lightweight parametric curves and surf…
RobustPointSet: A Dataset for Benchmarking Robustness of Point Cloud Classifiers
Saeid Asgari Taghanaki, Jieliang Luo, Ran Zhang +3
The 3D deep learning community has seen significant strides in pointcloud processing over the last few years. However, the datasets on which deep models have been trained have larg…
PointMask: Towards Interpretable and Bias-Resilient Point Cloud Processing
Saeid Asgari Taghanaki, Kaveh Hassani, Pradeep Kumar Jayaraman +2
Deep classifiers tend to associate a few discriminative input variables with their objective function, which in turn, may hurt their generalization capabilities. To address this, o…